Performance evaluation.  To quantitatively evaluate our reconstruction results, we followed
an n-way identification experiment [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, applied separately to images (RGB) and to depth maps (D).
Each reconstructed image is compared against \(n\)  candidate images (the ground truth image, and \((n-1)\)  other randomly selected images). The goal is to identify the ground truth, or at least rank it well among the candidates (rank=1 signifies perfect identification).
We evaluate our RGB or Depth reconstructions using this rank identification (lower is better). This provides an informative accuracy measure that accounts for cases when the ground truth is not strictly identified as the best candidate, but is nevertheless ranked fairly low.
Reconstructed Images (RGB) were compared against candidates using the image-based Perceptual Similarity metric of [7]}.
Reconstructed depth maps were compared against candidate depth maps using our new Depth-only Perceptual Similarity metric.
